Zusammenfassung
Data Science ist in aller Munde. Nicht nur wird an Konferenzen zu Big Data, Cloud Computing oder Data Warehousing darüber gesprochen: Glaubt man dem McKinsey Global Institute, so wird es alleine in den USA in den nächsten Jahren eine Lücke von bis zu 190.000 Data Scientists geben (Manyika et al. Big data: the next frontier for innovation, competition, and productivity, Report. www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation, 2011). In diesem Kapitel beleuchten wir daher zunächst die Hintergründe des Begriffs Data Science. Dann präsentieren wir typische Anwendungsfälle und Lösungsstrategien auch aus dem Big Data Umfeld. Schließlich zeigen wir am Beispiel des Diploma of Advanced Studies in Data Science der ZHAW Möglichkeiten auf, selber aktiv zu werden.
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Stockinger, K., Stadelmann, T. Data Science für Lehre, Forschung und Praxis. HMD 51, 469–479 (2014). https://doi.org/10.1365/s40702-014-0040-1
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DOI: https://doi.org/10.1365/s40702-014-0040-1